Column

1. R&D budget by department in 2017 ($b)

3. R&D budget over time by department ($b)

Column

2. Dept of Defense R&D budget by presidential party 1976-2017 ($b)

4. R&D budget by department over time cluster analysis

---
title: "U.S. Government R&D Budget"
output:
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
  html_document:
    df_print: paged
  word_document: default
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(ggthemes)
library(scales)
library(cluster)
library(dendextend)
library(ggdendro)

govt_raw <- read_csv ("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-02-12/fed_r_d_spending.csv")

govt_clean <- govt_raw %>%
   drop_na() %>%
   mutate_at (3:6, funs(round(./1000000000,1))) 
   

head(govt_clean,10)
```



Column {data-width=500}
-----------------------------------------------------------------------

### 1. R&D budget by department in 2017 ($b)

```{r}
govt_clean %>%
   filter (year == "2017") %>%
   ggplot(aes(x=reorder(department, rd_budget), y=rd_budget)) +
      geom_bar(stat='identity') +
      coord_flip() +
      theme_economist () +
      theme(axis.title.x = element_blank(),
            axis.title.y = element_blank(),
            legend.title = element_blank()) +
      labs(caption = "Source: American Association for the Advancement of Science")
```



### 3. R&D budget over time by department ($b)

```{r}
govt_clean %>%
   ggplot(aes(x=year, y=rd_budget, color=department)) +
      geom_point() +
      theme_economist () +
      theme(axis.title.x = element_blank(),
            axis.title.y = element_blank(),
            legend.title = element_blank(),
            legend.position = "right",
            legend.text=element_text(size=8)) +
      labs(caption = "Source: American Association for the Advancement of Science")
```

Column {data-width=500}
-----------------------------------------------------------------------
### 2. Dept of Defense R&D budget by presidential party 1976-2017 ($b)

```{r}
govt_clean %>%
   filter (department == "DOD") %>%
   ggplot () +
      geom_rect(aes(xmin=1974, xmax=1977, ymin=0,ymax=Inf, fill="Republican"), alpha=0.2) +
      geom_rect(aes(xmin=1977, xmax=1981, ymin=0,ymax=Inf, fill="Democrat"), alpha=0.2) +
      geom_rect(aes(xmin=1981, xmax=1993, ymin=0,ymax=Inf, fill="Republican"), alpha=0.2) +
      geom_rect(aes(xmin=1993, xmax=2001, ymin=0,ymax=Inf, fill="Democrat"), alpha=0.2) +
      geom_rect(aes(xmin=2001, xmax=2009, ymin=0,ymax=Inf, fill="Republican"), alpha=0.2) +
      geom_rect(aes(xmin=2009, xmax=2017, ymin=0,ymax=Inf, fill="Democrat"), alpha=0.2) +
      scale_fill_manual (values = c('blue','red')) +
   
      geom_line(aes (year, rd_budget)) +
   
      scale_x_continuous(breaks = seq(1976, 2017,4)) +
      theme_economist() +
      theme(axis.title.x = element_blank(),
            axis.title.y = element_blank(),
            legend.title = element_blank()) +
      labs(caption = "Source: American Association for the Advancement of Science")
```

### 4. R&D budget by department over time cluster analysis

```{r}
govt_spread <- govt_clean %>%
   select (department, year, rd_budget) %>%
   spread (year, rd_budget) %>%
   column_to_rownames("department")

govt_dist <- govt_spread %>%
   dist(method = 'euclidean') 

govt_clust <- govt_dist %>%
   hclust (method = 'complete') %>%
   as.dendrogram() %>%
   dendro_data(type="rectangle")

#ggplot(segment(govt_clust),labels=rownames(govt_clust)) + 
  #geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) + 
  #theme_dendro() +
  #coord_flip() +
  #scale_x_reverse()

ggdendrogram(govt_clust)
```